Beyond Body Mass Index. Is the Body Cell Mass Index (BCMI) a useful prognostic factor to describe nutritional, inflammation and muscle mass status in hospitalized elderly?

Rondanelli, Mariangela; Talluri, Jacopo; Peroni, Gabriella; Donelli, C.; Guerriero, F.; Ferrini, Krizia; Riggi, Emilia; Sauta, Elisabetta; Perna, Simone; Guido, Davide

doi:10.1016/j.clnu.2017.03.021

Cited by 28 publications

(23 citation statements)

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“…It is more sensitive than BMI in monitoring changes in muscle mass and protein in illnesscaused abnormality [34] [35]. In addition, it is a prognostic factor of the inflammation status and associated with skeletal muscle [35]. In our study, a decrease in MM, BCM, FFMI and BCMI was observed both in the ERAS and control group, demonstrating the protein breakdown and muscle loss during perioperative period.…”

Section: Discussionsupporting

confidence: 48%

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Evaluation of the effect of ERAS to nutritional status of patients with elective craniotomy using bioelectrical impedance analysis: a prospective and randomized controlled trial

Jin

Wang

et al. 2019

Preprint

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Background The aim of the present study was to test the body composition changes of patients undergoing elective craniotomy using bioelectrical impedance analysis, so as to evaluate the effect of enhanced recovery after surgery (ERAS) to nutritional status of patients. Methods 140 patients who needed elective craniotomy were randomly divided into two groups: observation group (ERAS group) and control group (traditional treatment group). The age was 45.6 ± 12.7 years old. Patients in ERAS group were treated with a set of enhanced recovery measures, while control group patients underwent conventional treatment. Bioelectrical impedance analysis was used to test body composition before and after the surgery. Results The body mass (BM), body mass index (BMI), fat mass (FM), muscle mass (MM), fat mass index (FMI), free-fat mass index (FFMI), body cell mass (BCM), body cell mass index (BCMI), in both groups were decreased after surgery. The decrease of FM and FMI in the control group was significantly different from that in the observation group (p<0.05). However, the decrease of BM, BMI, MM, FFMI, BCM and BCMI in both groups were not statistically significant. Conclusion Patients undergoing elective craniotomy showed various degrees of nutritional injuries, and ERAS could alleviate nutritional injuries caused by operation. Keywords Enhanced Recovery after Surgery • Bioelectrical impedance analysis • Elective craniotomy Trail Registration Chinese Clinical Trial Registry, ChiCTR-INR-16009662. Registered on 27 October 2016. Trail Registration Chinese Clinical Trial Registry, ChiCTR-INR-16009662. Registered on 27 October 2016.

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Section: Discussionsupporting

confidence: 48%

“…Similar to BMI FMI and FFMI BCMI also eliminates the influence associated with height. It is more sensitive than BMI in monitoring changes in muscle mass and protein in illnesscaused abnormality [34] [35]. In addition, it is a prognostic factor of the inflammation status and associated with skeletal muscle [35].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the effect of ERAS to nutritional status of patients with elective craniotomy using bioelectrical impedance analysis: a prospective and randomized controlled trial

Jin

Wang

et al. 2019

Preprint

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“…As shown in several other studies, a decrease in BMI is often indicative of a decrease in the muscle strength of the limbs (Perna et al, 2015;Rondanelli et al, 2017), and patients with sarcopenia generally have relative low BMI (Perez-Sousa et al, 2019). Therefore, a decline in BMI is an important manifestation of sarcopenia in patients undergoing surgery after fracture.…”

Section: Discussionmentioning

confidence: 82%

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Chen

Cai

Kang

et al. 2020

PeerJ

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Purpose To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China. Patients and methods We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment. Result We recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552–0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability. Conclusion Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

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“…As shown in several other studies, a decrease in BMI is often indicative of a decrease in the muscle strength of the limbs, 32,33 and patients with sarcopenia generally have relative low BMI. 34 Therefore, a decline in BMI is an important manifestation of sarcopenia in patients undergoing surgery after fracture.…”

Section: Discussionmentioning

confidence: 58%

Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

Chen

Tao

2019

Preprint

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Patients and methods:We conducted a community survey of patients aged ≥ 55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (Lasso analysis). The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We conducted internal sampling methods for qualitative assessment. Result:We recruited 61 participants (males: 20, mean age: 68.1 years). Various risk factors were assessed, and low body mass index and diabetes mellitus were identified as the most important risk factors (P<0.05).The model showed a good prediction rate (C-index: 0.909; 95% confidence interval: 0.81-1.00) and good correction effect. The C-index remained high (0.828) even after internal sample verification. Decision curve analysis showed that the risk of sarcopenia was 8.3-80.0%, suggesting good clinical practicability.Conclusion: Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, longer postoperative hospital stay, no higher education, no postoperative rehabilitation, removal of internal fixation, and less outdoor exercise.We believe that the AWGS criteria can be used to predict the occurrence of sarcopenia after patellar surgery by establishing an effective nomogram model.The aim of this study was to develop an effective and simple tool for predicting sarcopenia in patients undergoing post-fracture patellar surgery. Only the data available for period after the patient's hospitalization for fracture were used to evaluate the risk of sarcopenia in patients with patella fracture in order to study the effects of early prevention of sarcopenia and obtain accurate guidance for clinical work. Patients and methods PatientsThis study was designed as a retrospective investigation of the prognosis of elderly patients with patella fracture. conducted a questionnaire-based survey through appointment-based telephonic interview, outpatient services, and community follow-up. Data for all the patients were collected by the same researcher.Written informed consent was sought from all enrolled subjects before participation in the study; all participating patients provided consent. In this study, we included only fracture patients aged ≥ 55 years, since postoperative sarcopenia after fractures is rare in young patients. The laboratory blood test results taken into consideration were those obtained for the preoperative fasting samples of venous blood. Inclusion criteria and exclusion criteriaThe inclusion criteria for the survey were as follows: (1) diagnosis of sarcope...

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Beyond Body Mass Index. Is the Body Cell Mass Index (BCMI) a useful prognostic factor to describe nutritional, inflammation and muscle mass status in hospitalized elderly?

Cited by 28 publications

References 17 publications

Evaluation of the effect of ERAS to nutritional status of patients with elective craniotomy using bioelectrical impedance analysis: a prospective and randomized controlled trial

Evaluation of the effect of ERAS to nutritional status of patients with elective craniotomy using bioelectrical impedance analysis: a prospective and randomized controlled trial

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

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